THE VEHICLE ROUTING PROBLEM WITH STOCHASTIC DEMANDS IN AN URBAN AREA – A CASE STUDY

The vehicle routing problem with stochastic demands (VRPSD) is a combinatorial optimization problem. The VRPSD looks for vehicle routes to connect all customers with a depot, so that the total distance is minimized, each customer visited once by one vehicle, every route starts and ends at a depot, and the travelled distance and capacity of each vehicle are less than or equal to the given maximum value. Contrary to the classical VRP, in the VRPSD the demand in a node is known only after a vehicle arrives at the very node. This means that the vehicle routes are designed in uncertain conditions. This paper presents a heuristic and meta-heuristic approach for solving the VRPSD and discusses the real problem of municipal waste collection in the City of Niš

Ruteo de vehículos en el sector de hidrocarburos aplicando colonia de hormigas

En el sector de hidrocarburos existen operaciones que son realizadas de forma manual y sin ningún tipo de estudio u análisis previo antes de ser ejecutadas, lo cual genera que se realicen actividades ineficientes que producen costos extras a la compañía. Una de estas actividades es la logística en la distribución de productos, esto se debe a que no existe un criterio de contratación de vehículos establecido que permita analizar las posibles opciones de contratación de vehículos para que realicen el proceso de distribución. Para esto, se realizará la programación de vehículos encargados de hacer la entrega de los productos mediante una meta-heurística Ant Colony Optimization, la cual buscará dar una solución, teniendo como punto de referencia el modelo matemático exacto que permita identificar el desempeño de la meta- heurística, teniendo en cuenta que el modelo debe estar en la capacidad de cumplir con la demanda de los clientes y disminuir el costo de la operación actual, en al menos un 5% para que el impacto de la implementación sea efectivo.In the hydrocarbon sector there are operations that are performed manually and without any prior study or analysis before being executed, which leads to inefficient activities that produce extra costs to the company. One of these activities is the logistics in the products distribution; this is due to the fact that there is no criterion for hiring vehicles that allows analyzing the possible options for hiring vehicles to carry out the distribution process. For this, the programming of vehicles in charge of delivering the products will be carried out through an Ant Colony Optimization meta-heuristic, which will seek to provide a solution, taking as a point of reference the exact mathematical model to identify the performance of the meta-heuristic, taking into account that the model must be able to meet customer demand and reduce the cost of the current operation.Ingeniero (a) IndustrialPregrad

Razvoj logističkog modela za upravljanje komunalnim otpadom primenom heurističkih metoda

Inadequate collection and transport, as functions of municipal waste management, result in enormous economic and ecological losses, and represent a significant incentive to a great number of researchers with the aim of discovering appropriate systemic solutions. A set of vehicles that support the process of collection and transport of municipal waste most often comprise the majority of vehicle fleets of public utility companies, which is usually around 50–70% of transport units. This process is also dominant in those business systems that integrate several public utilities. In such systems, there are 15–40% of transport units that support the process of collection and transport of municipal waste. Through optimization and application of heuristic and metaheuristic methods on only one of these systems, it is possible to reduce the cost of fuel for vehicles by 10 ÷ 25%. The choice of the optimal logistic model for collection and transport of municipal waste in urban areas implies the consideration of a large number of limitations. This number has imposed the need for the application of various algorithms for obtaining optimal solutions. In this dissertation, for the purpose of obtaining an optimal logistic model of collection and transport of municipal waste, the C-W savings algorithm was applied to yield an initial solution, while its improvement was performed by applying the 2-OPT search algorithm and the SA algorithm. The dissertation presents four models, whose simulation led to the optimal model that represents the dynamic model of vehicle routing for collection and transport of municipal waste. The developed methodology was applied to a real problem of waste collection and transport in the City of Niš, and the obtained results show the achieved reduction in fuel for vehicles and operation time of 10%. Thus developed model served as the basis for the development of a conceptual expert system model that predicts the use of information and communication technologies in the design of optimal routes in real time. Such a model can help companies that deal with waste collection and transport to achieve even greater fuel savings and reduction in operating costs